Bending of stochastic Kirchhoff plates on Winkler foundations via the Galerkin method and the Askey-Wiener scheme

In this paper, the method of Galerkin and the Askey-Wiener scheme are used to obtain approximate solutions to the stochastic displacement response of Kirchhoff plates with uncertain parameters. Theoretical and numerical results are presented. The Lax-Milgram lemma is used to express the conditions for existence and uniqueness of the solution. Uncertainties in plate and foundation stiffness are modeled by respecting these conditions, hence using Legendre polynomials indexed in uniform random variables. The space of approximate solutions is built using results of density between the space of continuous functions and Sobolev spaces. Approximate Galerkin solutions are compared with results of Monte Carlo simulation, in terms of first and second order moments and in terms of histograms of the displacement response. Numerical results for two example problems show very fast convergence to the exact solution, at excellent accuracies. The Askey-Wiener Galerkin scheme developed herein is able to reproduce the histogram of the displacement response. The scheme is shown to be a theoretically sound and efficient method for the solution of stochastic problems in engineering. (C) 2009 Elsevier Ltd. All rights reserved.

Chaos-Galerkin solution of stochastic Timoshenko bending problems

This paper presents an accurate and efficient solution for the random transverse and angular displacement fields of uncertain Timoshenko beams. Approximate, numerical solutions are obtained using the Galerkin method and chaos polynomials. The Chaos-Galerkin scheme is constructed by respecting the theoretical conditions for existence and uniqueness of the solution. Numerical results show fast convergence to the exact solution, at excellent accuracies. The developed Chaos-Galerkin scheme accurately approximates the complete cumulative distribution function of the displacement responses. The Chaos-Galerkin scheme developed herein is a theoretically sound and efficient method for the solution of stochastic problems in engineering. (C) 2011 Elsevier Ltd. All rights reserved.

Galerkin Solution of Stochastic Beam Bending on Winkler Foundations

In this paper, the Askey-Wiener scheme and the Galerkin method are used to obtain approximate solutions to stochastic beam bending on Winkler foundation. The study addresses Euler-Bernoulli beams with uncertainty in the bending stiffness modulus and in the stiffness of the foundation. Uncertainties are represented by parameterized stochastic processes. The random behavior of beam response is modeled using the Askey-Wiener scheme. One contribution of the paper is a sketch of proof of existence and uniqueness of the solution to problems involving fourth order operators applied to random fields. From the approximate Galerkin solution, expected value and variance of beam displacement responses are derived, and compared with corresponding estimates obtained via Monte Carlo simulation. Results show very fast convergence and excellent accuracies in comparison to Monte Carlo simulation. The Askey-Wiener Galerkin scheme presented herein is shown to be a theoretically solid and numerically efficient method for the solution of stochastic problems in engineering.

Dynamics of sulfidogenesis associated to methanogenesis in horizontal-flow anaerobic immobilized biomass reactor

Two bench-scale horizontal anaerobic fixed bed reactors were tested to remove both sulfate and organic matter from wastewater. First, the reactors (R1 and R2) were supplied with synthetic wastewater containing sulfate and a solution of ethanol and volatile fatty acids. Subsequently, RI and R2 were fed with only ethanol or acetate, respectively. The substitution to ethanol in R1 increased the sulfate reduction efficiency from 83% to nearly 100% for a chemical oxygen demand to sulfate (COD/sulfate) ratio of 3.0. In contrast, in R2, the switch in carbon source to acetate strongly decreased sulfidogenesis and the maximum sulfate reduction achieved was 47%. Process stability in long-term experiments and high removal efficiencies of both organic matter and sulfate were achieved with ethanol as the sole carbon source. The results allow concluding that syntrophism instead of competition between the sulfate reducing bacteria and acetoclastic methanogenic archaeal populations prevailed in the reactor. (C) 2009 Elsevier Ltd. All rights reserved.

Performance of a horizontal-flow anaerobic immobilized biomass (HAIB) reactor and dynamics of the microbial community during degradation of pentachlorophenol (PCP)

The anaerobic biological treatment of pentachlorophenol (PCP) and methanol as the main carbon source was investigated in a horizontal-flow anaerobic immobilized biomass (HAIB) reactor at 30 +/- 1 degrees C, during a 220-day trial period. The reactor biomass was developed as an attached biofilm on polyurethane foam particles, with 24 h of hydraulic retention time. The PCP concentrations, which ranged from 2.0 to 13.0 mg/L, were controlled by adding synthetic substrate. The HAIB reactor reduced 97% of COD and removed 99% of PCP. The microbial biofilm communities of the HAIB reactor amended with PCP, without previous acclimatization, were characterized by polymerase chain reaction (PCR) and amplified ribosomal DNA restriction analysis (ARDRA) with specific Archaea oligonucleotide primers. The ARDRA technique provided an adequate analysis of the community, revealing the profile of the selected population along the reactor. The biomass activities in the HAIB reactor at the end of the experiments indicated the development of PCP degraders and the maintenance of the population of methanogenic Archaea, ensuring the high efficiency of the system treating PCP with added methanol as the cosubstrate. The use of the simplified ARDRA method enabled us to monitor the microbial population with the addition of high concentrations of toxic compounds and highlighting a selection of microorganisms in the biofilm. (C) 2008 Published by Elsevier Ltd.

The influence of immobilized biomass and particle size on the fluid dynamics of an anaerobic fluidized bed reactor

Fluid dynamic analysis is an important branch of several chemical engineering related areas, such as drying processes and chemical reactors. However, aspects concerning fluid dynamics in wastewater treatment bioreactors still require further investigation, as they highly influence process efficiency. Therefore, it is essential to evaluate the influence of biofilm on the reactor fluid dynamic behavior, through the analysis of a few important parameters, such as minimum fluidization velocity, bed expansion and porosity, and particle terminal velocity. The main objective of the present work was to investigate the fluid dynamics of an anaerobic fluidized bed reactor, having activated carbon particles as support media for biomass immobilization. Reactor performance was tested using synthetic residual water, which was prepared using the solution employed in BOD determination. The results showed that the presence of immobilized biomass increased particle density and altered the main fluid dynamic parameters investigated.

An exact conserving algorithm for nonlinear dynamics with rotational DOFs and general hyperelasticity. Part 2: shells

Following the approach developed for rods in Part 1 of this paper (Pimenta et al. in Comput. Mech. 42:715-732, 2008), this work presents a fully conserving algorithm for the integration of the equations of motion in nonlinear shell dynamics. We begin with a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, allowing for an extremely simple update of the rotational variables within the scheme. The weak form is constructed via non-orthogonal projection, the time-collocation of which ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that general hyperelastic materials (and not only materials with quadratic potentials) are permitted in a totally consistent way. Spatial discretization is performed using the finite element method and the robust performance of the scheme is demonstrated by means of numerical examples.

An exact conserving algorithm for nonlinear dynamics with rotational DOFs and general hyperelasticity. Part 1: Rods

A fully conserving algorithm is developed in this paper for the integration of the equations of motion in nonlinear rod dynamics. The starting point is a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, which results in an extremely simple update of the rotational variables. The weak form is constructed with a non-orthogonal projection corresponding to the application of the virtual power theorem. Together with an appropriate time-collocation, it ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that nonlinear hyperelastic materials (and not only materials with quadratic potentials) are permitted without any prejudice on the conservation properties. Spatial discretization is performed via the finite element method and the performance of the scheme is assessed by means of several numerical simulations.

Study of the influence of simultaneous variation of magnetic material microstructural features on domain wall dynamics

The magnetic Barkhausen noise (MBN) is a phenomenon sensitive to several kinds of magnetic material microstructure changes, as well as to variations in material plastic deformation and stress. This fact stimulates the development of MBN-based non-destructive testing (NDT) techniques for analyzing magnetic materials, being the proposition of such a method, the main objective of the present study. The behavior of the MBN signal envelope, under simultaneous variations of carbon content and plastic deformation, is explained by the domain wall dynamics. Additionally, a non-destructive parameter for the characterization of each of these factors is proposed and validated through the experimental results. (C) 2010 Elsevier B.V. All rights reserved.

Flow Visualization in Arteriovenous Fistula and Aneurysm Using Computational Fluid Dynamics

The arteriovenous fistula (AVF) is characterized by enhanced blood flow and is the most widely used vascular access for chronic haemodialysis (Sivanesan et al., 1998). A large proportion of the AVF late failures are related to local haemodynamics (Sivanesan et al., 1999a). As in AVF, blood flow dynamics plays an important role in growth, rupture, and surgical treatment of aneurysm. Several techniques have been used to study the flow patterns in simplified models of vascular anastomose and aneurysm. In the present investigation, Computational Fluid Dynamics (CFD) is used to analyze the flow patterns in AVF and aneurysm through the velocity waveform obtained from experimental surgeries in dogs (Galego et al., 2000), as well as intra-operative blood flow recordings of patients with radiocephalic AVF ( Sivanesan et al., 1999b) and physiological pulses (Aires, 1991), respectively. The flow patterns in AVF for dog and patient surgeries data are qualitatively similar. Perturbation, recirculation and separation zones appeared during cardiac cycle, and these were intensified in the diastole phase for the AVF and aneurysm models. The values of wall shear stress presented in this investigation of AVF and aneurysm models oscillated in the range that can both cause damage to endothelial cells and develop atherosclerosis.

Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence

We examine the representation of judgements of stochastic independence in probabilistic logics. We focus on a relational logic where (i) judgements of stochastic independence are encoded by directed acyclic graphs, and (ii) probabilistic assessments are flexible in the sense that they are not required to specify a single probability measure. We discuss issues of knowledge representation and inference that arise from our particular combination of graphs, stochastic independence, logical formulas and probabilistic assessments. (C) 2007 Elsevier B.V. All rights reserved.

DEVELOPMENT OF STATIC MIXERS FOR MISCIBLE FLUIDS IN LAMINAR FLOW WITH THE USE OF COMPUTATIONAL FLUID DYNAMICS (CFD)

Static mixers with improved performance were developed from CFD simulations in a stepwise approach. The relevant geometric features of simple mixer designs and the corresponding mixing mechanisms-laminar shear, elongational flow, and distributive mixing-were identified first. This information was used to formulate guidelines for the development of new geometries. The solid elements of the static mixer should: (a) provide restrictions to the flow; (b) deflect the flow; (c) be sequentially rotated around the flow direction to provide symmetry; (d) extend from the center of the pipe to the vicinity of the walls to avoid short-circuiting; and (e) distribute and remix the flow. Based on these guidelines, two improved mixer designs were developed: the DS A-I mixer has a good mixing efficiency and an acceptable pressure drop; the Fins 35 degrees mixer is more efficient and compact, but requires a larger pressure drop. Their performance indicates that their use is possible on industrial applications.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

Stochastic stability analysis for the constant-modulus algorithm

We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.

Self-organized criticality and the predictability of human behavior

The behavior of normal individuals and psychiatric patients vary in a similar way following power laws. The presence of identical patterns of behavioral variation occurring in individuals with different levels of activity is suggestive of self-similarity phenomena. Based on these findings, we propose that the human behavior in social context can constitute a system exhibiting self-organized criticality (SOC). The introduction of SOC concept in psychological theories can help to approach the question of behavior predictability by taking into consideration their intrinsic stochastic character. Also, the ceteris paribus generalizations characteristic of psychological laws can be seen as a consequence of individual level description of a more complex collective phenomena. Although limited, this study suggests that, if an adequate level of description is adopted, the complexity of human behavior can be more easily approached and their individual and social components can be more realistically modeled. (C) 2009 Elsevier Ltd. All rights reserved.